A 5 Hz limit for the detection of temporal synchrony in vision

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1 A 5 Hz limit for the detection of temporal synchrony in vision Michael Morgan 1 (Applied Vision Research Centre, The City University, London) Eric Castet 2 ( CRNC, CNRS, Marseille) 1 Corresponding Author Applied Vision Research Centre, The City University, Northampton Square, London EC1V0HB; 2 Centre de Recherche en Neurosciences Cognitives (CRNC), UPR 9012 du CNRS, 31 chemin J. Aiguier, 13402, Marseille cedex 20, France. 1

2 Summary We used textures of randomly-moving grating patches to assess the role of fine-grain temporal synchrony in texture segregation. In the target area, patches reversed direction simultaneously. In the surround, patches changed direction at random times. Thus phase changes in the target area were precisely synchronous, while those in the surround were not. We found that the target area was frequently visible, and that observers could discriminate its shape (horizontal vs vertical) at frame rates of 100 Hz in exposures as short as 20 frames. To eliminate contrast and motion cues completely, we made all the background elements identical to the target elements, but with random starting phase. Despite the presence of synchrony in the target area but not the background, the target was generally very hard to see. Targets that remained visible contained low temporal frequency modulations of direction. We conclude that the human observer can detect synchrony, but only up to temporal frequencies of about 5 Hz once motion and contrast artifacts have been eliminated. 2

3 1. Introduction Physiologists and psychophysicists have become interested in the possibility that precise temporal synchrony of nerve impulses in different parts of the brain is the solution to the binding problem by which different attributes such as shape and colour, are seen to belong to the same object (Castelo-Branco, Goebel, Neuenschwander, & Singer, 2000; Singer, 1999a, 1999b; Usher & Donnelly, 1998). The suggestion has been controversial (Lee & Blake, 1999b; Shadlen & Movshon, 1999). On general grounds, it is evident that the temporal dimension is important in object recognition (Kant, 1787): We would not perceive the Cheshire Cat (Carroll, 1865) if its grin, body and colour appeared in appropriately adjacent locations on different days. What is at issue is the fineness of temporal synchrony used for grouping. There have been claims that very fine grain synchrony in the millisecond region facilitate object segregation (Lee & Blake, 1999b; Usher & Donnelly, 1998). Lee & Blake used fields of grating patches (see Fig. 1) within which the phase of the grating changed on every frame at a 100 Hz refresh rate. The direction of the phase change in relation to the change in the previous frame was random, but was the same for all elements in the target area. Elements in the background changed their phase according to independent motion reversal sequences (point processes). Thus, all the elements in the target area changed their motion direction synchronously, while those in the background changed direction asynchronously. Since the orientation of all the elements was random, and since the direction of the first phase displacement was also random, it was argued that segregation of the target area could not be based upon motion direction cues. However, Farid and Adelson (2000) pointed out that low-pass temporal filtering might suffice to explain segregation in the Lee and Blake stimulus. If a grating changes its phase between 0 and 90 deg at a sufficiently high rate, its apparent contrast is reduced because the two phases effectively summate. In general, any point process generating phase change will produce a contrast that is particular to that point process. Since all the elements in the target area are generated by the same point process, they will have the same apparent contrast, while those in the background will produce a patchy contrast. Segregation could therefore be based upon contrast-variance discrimination following temporal filtering. When we examined stimuli generated by the methods described by Lee & Blake, it was obvious that they were very different in difficulty, depending on the seed given to the random number generator. The seed determines the reversal sequence for all the elements in the target area, the sequence in the background, the initial displacement direction of each element, and the distribution of orientations. To look at the effect of these separately, we fixed the reversal sequence for the target area, leaving the sequences in the background random. The orientation distribution was Gaussian with a mean of 90 deg (vertical) and standard deviation 45 deg. Three different seeds were chosen to determine the orientations of the patches and these were randomly interleaved over a series of 300 trials, with 5 different exposure durations and two possible target orientations (horizontal vs vertical). To investigate the effects of contrast, the elements either had all the same contrast (1.0) or their contrast was randomly sampled from a uniform distribution with mean 0.5 and range

4 2. Methods Stimuli were presented on a Sony Trinitron RGB monitor (GDM-F500T9) under control of a Cambridge Research Systems VSG 2/3F board in a host PC. The monitor refresh rate was 100 Hz. Programs for generating the stimuli were written in MATLAB. Each frame of the display consisted of a 26 x 26 array of Gabor patches, each containing a 5.8 Cycle/deg sinusoidal grating windowed with a Gaussian envelope. The mean luminance of the patches was 36 cd/m 2 and unless otherwise stated the Michelson contrast was 1.0. The overall dimension of each frame was 7.55 deg 2, viewed from 2m. The orientation of each patch was chosen randomly from a Gaussian distribution with mean 90 deg (vertical) and standard deviation 45 deg (unless otherwise stated). The phase of the gratings was randomised within patches in the range 0-2 Sequences of 20 frames were stored in the VSG DRAM in which the phase of the grating was changed on each frame by +/- one fifth of the grating cycle). This resulted in an irregular series of motion steps in which the grating either moved in the same (+) or opposite (-) direction to the previous step. The probability of + and steps were equal. We refer to the resulting series of steps as the point process (c.f. Lee & Blake) for that element. All the elements in the target area had the same point process; those in the background were randomly selected, unless otherwise stated. The direction of the first phase shift was randomised over elements, unless otherwise stated. The target area was either horizontal (8 x 4 patches) or vertical (4 x 8 patches) and was placed in the centre of one of three screen quadrants: top left, bottom right or bottom left (shortage of DRAM memory prevented use of all the quadrants, since all the possible stimulus sequences were computed and stored before each experiment). The target position was randomised over trials and the observer's task was to report whether target orientation was horizontal or vertical (not its position). Exposure duration was 200, 600, 1000, 1400 or 1800 msec, unless stated otherwise. A full 20 frame sequence took 200 msec. Longer durations were obtained by wrap-around, which must be taken into account when assessing the point process. Each combination of exposure, screen position, and orientation was repeated 10 times inside a block of 200 trials. At the end of each block the screen went blank and the observer took a rest. At a given screen position, the point processes of the elements was always the same within a block, so we could determine the effects of the point process by analysing positions separately. There was no fixation point and the observer was free to make eye movements to search the display. There was no error feedback, unless stated otherwise. Careful note was taken of all the seeds used to start the random number generators so that every experimental condition could be reproduced. The frame sequences can be obtained as MATLAB images from 3. Results Because there was little effect of exposure duration on accuracy, the results for the different exposures have been combined (Fig. 2). Easy sequences were those in which there were long run lengths in the same direction in the target area (e.g., LLLLLL...) or those in which there was rapid alternation (e.g. LRLRLR...). There was thus a U- shaped relationship between visibility and temporal frequency of alternation. By inspection, long run sequences were visible because they were of uniformly low contrast and because they presented a strong motion signal. 4

5 Alternating sequences were visible because they appeared stationary, or to shiver slightly. The high visibility of long runs and alternations agrees with the suggestion that contrast is an important cue for segregation (Farid & Adelson, 2000), since these sequences would be expected to have low and high time-averaged contrast respectively. However, we doubted whether contrast was the whole story, since the most obvious subjective cue from the alternating sequences was motion, not contrast. Lee & Blake (1999a) reported that contrast randomization over elements had little effect. With our controlled reversal sequences, we found a more complex story. Contrast randomization had no effect on the alternating sequences for both observers, and no effect on the longest run length for one of the observers (EC). Both observers were strongly affected by contrast randomization at intermediate temporal frequencies of reversal. These data were obtained with extreme randomization, which made a proportion of the elements invisible. When less extreme randomization was used, there was no effect of contrast randomization in the range on the visibility of the long sequence, even for observer MM (Fig. 3). We conclude that both contrast and motion are cues for object segregation. We could not rule out temporal synchrony as an additional cue. To isolate synchrony from all other cues, we devised a new way to generate the display. First, a series of frames defining the target area was generated, exactly as before. Then the background was generated, selecting every background patch from the set of target patches, but with a random starting frame. For example, if all the target patches had the sequence LLLLRRLLLLRR..., a particular background patch might have the sequence LLRRLLLLRR... and another background patch the sequence RRLLLLRRLLLL... Thus, all the target patches changed direction synchronously while those in the background had exactly the same temporal frequencies of reversal, but changed asynchronously. There was no possibility of a contrast cue or a motion cue in these stimuli, and none was ever seen. The results are easily summarized without the aid of a figure. None of the sequences visible in the first Experiment (Fig. 2) could be seen at all in this experiment. Most randomly-determined reversal sequences were invisible as well, with the rare exception. In these exceptional cases, the target area seemed to undergo a low temporal frequency pulsation. Inspection revealed that these cases had runs alternating with stationary flicker. To check this, we examined the visibility of the sequence LLLLLLLLLLRLRLRLRLRL. The Fourier spectrum of this stimulus shows a strong periodicity at 5 Hz (note that the full sequence length is 20 * 10 =200 msec). The target was highly visible to EC (96 % correct across durations and across 3 different seeds) and could be seen by MM in long exposure, although it failed to 'pop out' convincingly. 4. Conclusions We conclude that synchrony of relatively low temporal frequency modulations of motion/contrast can be the basis for segregation, in spite of some differences between observers, but that the temporal grain is two orders of magnitude coarser than the ~ 1 msec synchrony suggested by other authors. A recent study also suggests that only modest synchrony can be effective. Kandil & Fahle (2000) found that synchronously rotating elements could be segregated from an asynchronous background at a rate of 8 Hz but not at 32 Hz. There is no evidence in our data for a role of synchrony at rates greater than about 5 Hz, when the first and second moments of the contrast/motion statistics are controlled. In the case of segregation of static stimuli by orientation we have a good understanding of the statistical regularities that can and cannot be extracted by the observer (Dakin & Watt, 1997). An equivalent understanding of spatio-temporal statistics is now needed, rather than the inspection of uncontrolled randomness. 5

6 6

7 Figure Legends Fig. 1. The figure shows an actual example of one frame of the stimulus used in our experiments. In the next frame, all the Gabor elements would phase shift by +/- 72 deg, the direction being random over elements. In following frames, changes in direction would be synchronous for elements in the target area, but asynchronous in the background. The target area (invisible here) was an 8 x 4 or 4 x 8 array of patches in the centre of one the 4 quadrants of the display. 7

8 Fig. 2 Results from the first experiment, examining the visibility of different reversal sequences (vertical axis) in fixed Vs random contrast conditions. Results are shown separately for two observers (MM Top, EC Bottom). The legend inside each bar indicates the motion sequence of one of the elements in the target area. L refers to an arbitrary direction in space depending on patch orientation, which was randomised, and R is the opposite direction. Note that the actual direction of each element is determined randomly, so that LLLL.. for one element could be RRRR.. for another. 0 LLLLLLLLLLLLLLLLLLLL 10 LLLLLLLLLRRRRRRRRRRL Reversal Frequency, Hz LLLLRRRRRLLLLLRRRRRL LLLRRRRLLLLRRRRLLLLR LLRRRLLLRRRLLLRRRLLL LRRLLRRLLRRLLRRLLRRL LRLRLRLRLRLRLRLRLRLR EC Contrast Random Fixed P Correct 0 LLLLLLLLLLLLLLLLLLLL Reversal Frequency, Hz 10 LLLLLLLLLRRRRRRRRRRL 20 LLLLRRRRRLLLLLRRRRRL 25 LLLRRRRLLLLRRRRLLLLR 33 LLRRRLLLRRRLLLRRRLLL 50 LRRLLRRLLRRLLRRLLRRL 100 LRLRLRLRLRLRLRLRLRLR MM Contrast Random Fixed P Correct 8

9 Fig. 3 Effects of contrast randomisation on visibility of a continuous motion sequence for observer MM. The contrast of each patch was chosen from a uniform distribution with upper limit 1.0 and a range indicated on the horizontal axis P Correct MM Sequence LLLLLLLLLLLLLLLLLLLL Contrast Range 9

10 References Carroll, L. (1865). Alice's Adventures in Wonderland. Castelo-Branco, M., Goebel, R., Neuenschwander, S., & Singer, W. (2000). Neural synchrony correlates with surface segregation rules. Nature, 405(6787), Dakin, S. C., & Watt, R. J. (1997). The computation of orientation statistics from visual texture. Vision Research, 37, Farid, H., & Adelson, E. H. (2000). Standard mechanisms can explain grouping in temporall synchronous displays. Investigative Ophthalmology and Visual Science, 4, S438. Kandil, F., & Fahle, M. (2000). Perception, 29, 114. Kant, I. (1787). The Critique of Pure Reason, 2 nd Edition; Translated by Norman Kemp Smith. Lee, S.-H., & Blake, R. (1999a). Science, 286, Lee, S.-H., & Blake, R. (1999b). Visual form created solely from temporal structure. Science, 284, Shadlen, M. N., & Movshon, J. A. (1999). Synchrony unbound: a critical evaluation of the temporal binding hypothesis. Neuron, 24(1), 67-77, Singer, W. (1999a). Neuronal synchrony: a versatile code for the definition of relations? Neuron, 24(1), 49-65, Singer, W. (1999b). Time as coding space? Curr Opin Neurobiol, 9(2), Usher, M., & Donnelly, N. (1998). Visual synchrony affects binding and segmentation in perception. Nature, 394(6689),

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